A system for characterizing at least one particle from a fluid sample is disclosed. The system includes a filter disposed upstream of an outlet, and a luminaire configured to illuminate the at least one particle at an oblique angle. An imaging device is configured to capture and process images of the illuminated at least one particle as it rests on the filter for characterizing the at least one particle. A system for characterizing at least one particle using bright field illumination is also disclosed. A method for characterizing particulates in a fluid sample using at least one of oblique angle and bright field illumination is also disclosed.

According to an embodiment of the present invention, there is provided a method of screening a prostate cancer patient by optical image analysis of a circulating tumor cell marker and a prostate-specific membrane antigen.

The present invention relates to a method for subjecting a plurality of microwells containing cells to a high-content assay, said method comprising: a) Acquiring at least one image of said plurality of microwells; b) In said image, detecting a plurality of areas of interest, each area of interest corresponding to a single cell; c) Measuring at least one derived property, and, optionally, at least one direct property of said areas of interest, where said one or more properties is a selection property; d) Selecting a subset of said plurality of microwells, where said microwells belonging to the subset contain areas of interest selected based on said at least one selection property; e) Extrapolating an output parameter from a property measured in the set of areas of interest selected, where said property is defined as output property, said output property being distinct from said selection properties where said output parameter is the processing of an output property measured in said set of areas of interest. In a further aspect, there are claimed a system for subjecting a plurality of microwells containing cells to a high-content assay and a computer program which comprises instructions for subjecting a plurality of microwells containing cells to a high-content assay.

The present invention extends to methods, systems, and computer program products for estimating oocyte quality. A machine learning algorithm accesses oocyte training data for a mammalian species (e.g., humans) and trains a neural network to estimate oocyte quality for the mammalian species based on the oocyte training data. The neural network accesses a microscopic image of an oocyte and identifies oocyte features of the oocyte. Based on the identified oocyte features, the neural network estimates oocyte quality, including: (a) predicting a probability of a corresponding embryo maintaining sufficient developmental competence until a specified time after fertilization and (b) predicting another probability of the corresponding embryo reaching a specific embryonic stage after fertilization. An oocyte is selected, from among a plurality of human oocytes including the human oocyte, for a potential recipient based at least in part on the oocyte quality, including based on the probability and the other probability.

A system for selective microcapsule extraction includes a non-planar core-shell microfluidic device. The non-planar core-shell microfluidic device generates microcapsules defining a core-shell configuration. A subset of the microcapsules contain aggregates, tissues, or at least one cell. A camera captures images of the microcapsules. A detection module includes a processor and a memory. The memory includes instructions that when executed by the processor causes the detection module to provide the images of the microcapsules as an input to a machine learning model. The machine learning model identifies microcapsules containing aggregates, tissues, or at least one cell. A force generator generates a force to extract the microcapsules. A microcontroller selectively activates the force generator to generate the force when the detection module identifies a microcapsule containing aggregates, tissues, or at least one cell to extract the microcapsule.

A portable air quality monitoring device is disclosed that can identify the type of particles in the air. This device takes images of particles in the air and compares them with a library of particles in its memory to identify the type of particles. The device has a housing that draws ambient air into the system and takes microscopic images of the flowing particles and droplets using flash photography. The device can be stand alone or can connect to the back of a mobile phone and use the mobile phone camera and light. People can upload their local air quality data online for all to see the local air quality.

Aspects of the present disclosure include a method for sorting cells of a sample based on an image of a cell in a flow stream. Methods according to certain embodiments include detecting light from a sample having cells in a flow stream, generating an image mask of a cell from the sample and sorting the cell based on the generated image mask. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to generate an image mask of a cell in a sample in a flow stream and to sort the cell based on the generated image mask are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for generating an image mask and for determining one or more features of the cell are also provided.

Methods and systems for determining interaction between cells are described wherein the method includes determining or receiving a sequence of images representing manipulating first cells, in a holding space, the holding space including a functionalized wall comprising second cells, the manipulating including settling of the first cells onto the functionalized wall and applying a force on the settled first cells; detecting groups of pixels representing first cells in first images representing the settling of the first cells onto the functionalized wall; tracking locations of detected first cells in the first images; and, determining settling events, a settling event being determined if a cell in a first image is not distinguishable from background of the first image, the location in the image at which a cell settling event is detected defining a cell settling location; detecting groups of pixels representing cells in second images captured during the application of the force and tracking locations of detected cells, wherein tracked locations of a detected cell in the second images form a tracking path, the first location of the tracking path defining a pop-up event, the location in a second image at which a pop-up event is detected defining a pop-up location; and, determining detachment events based on the settling locations and based on the pop-up locations, a detachment event defining a first cell being detached from a second cell due to application of the force on the first cell, and determining information about the interaction between first and second cells based on the force applied to the first cells.

A fluorescence image analyzer has an imaging unit for capturing a first image containing at least a part of a region of a cell as an imaging target for a plurality of cells in a sample in which a target site on a chromosome is labeled with a fluorescent dye, and a second image including fluorescence generated from a fluorescent dye labeling the target site of the cell of the first image. The processing unit selects a plurality of test cells having specific morphological characteristics to be tested from a plurality of cells based on at least the first image, and extracts the bright spots of fluorescence generated from the fluorescent dye. The processing unit identifies cells with chromosomal abnormalities and/or cells without chromosomal abnormalities based on the extracted bright spots, and generates information related to the ratio of cells with chromosomal abnormalities relative to the test cells.

Disclosed is a method for processing Raman data of eosinophil based on artificial intelligence, the method being executed by a device, the method including generating Raman data by performing Raman analysis using a specific wavelength on eosinophils isolated from blood of a diagnosed person, pre-processing the generated Raman data, assigning a weight to the pre-processed Raman data for each of components including a nucleus, a cell membrane, a granule, and a background, classifying data for each component based on a result of assigning the weight, extracting data in which the component is the granule based on a classified result; and determining whether a specific disease has occurred in the diagnosed person through eosinophil characteristics of the diagnosed person based on the extracted data.